104 results

1. Lab Featured

   Managing Terraform State

   In this hands-on lab you will import existing infrastructure, write Terraform configuration that matches that infrastructure, and manipulate state storage with Terraform.

2. Lab Featured

   Entity and Sentiment Analysis with the Natural Language API

   The Cloud Natural Language API lets you extract entities, and perform sentiment and syntactic analysis on a block of text. In this hands-on lab you’ll learn how to extract entities and sentiment from text using the Cloud Natural Language API.

3. Lab Featured

   Cloud Functions: Qwik Start - Console

   This hands-on lab shows you how to create and deploy a Cloud Function using the Cloud Platform Console. Watch the short video Connect & Extend GCP Services with Google Cloud Functions.

4. Lab Featured

   Getting Started with the Vertex AI Gemini API and Python SDK

   In this lab, you will learn how to use the Vertex AI SDK for Python to call the Vertex AI Gemini API.

5. Lab Featured

   Introduction to SQL for BigQuery and Cloud SQL

   In this lab, you learn fundamental SQL clauses and get hands-on practice running structured queries on BigQuery and Cloud SQL.

6. Lab Featured

   Implementing Security in Dataplex

   This lab shows you how to implement security in Dataplex.

7. Lab Featured

   Interact with Terraform Modules

   In this hands-on lab you will create and use Terraform modules to organize your cloud configuration.

8. Lab Featured

   Deploy a Compute Instance with a Remote Startup Script: Challenge Lab

   Configure a Linux Google Compute Engine instance that installs an Apache web server software using a remote startup script, then confirm that Apache has successfully installed.

9. Lab Featured

   Infrastructure as Code with Terraform

   In this hands-on lab you will build, change, provision, and destroy infrastructure using Terraform in the cloud environment.

10. Lab Featured

    Orchestrating the Cloud with Kubernetes (AWS)

    In this lab you will learn how to provision a complete Kubernetes cluster using Google Kubernetes Engine; deploy and manage Docker containers using kubectl; and break an application into microservices using Kubernetes Deployments and Services.